Topic
Ranking (information retrieval)
About: Ranking (information retrieval) is a research topic. Over the lifetime, 21109 publications have been published within this topic receiving 435130 citations.
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24 Feb 2012TL;DR: In this paper, the authors propose a system to identify a source with which each of the links is associated and rank the list of links based at least in part on the quality of the identified sources.
Abstract: A system ranks results. The system may receive a list of links. The system may identify a source with which each of the links is associated and rank the list of links based at least in part on a quality of the identified sources.
208 citations
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IBM1
TL;DR: In this article, an automated system optimizes selection of sources in a distributed information system for query searching, where a training set of documents is created for each source by randomly selecting significant portions of the documents thereof.
Abstract: In an information retrieval system, an automated system optimizes selection of sources in a distributed information system for query searching. A training set of documents is created for each source by randomly selecting significant portions of the documents thereof. A test set documents is created for each source from the documents not included in the training set. Each document in the training and test set is defined in terms of features/attributes and a name as samples representing individual sources. Pattern recognizing means process the samples to recognize patterns in the documents to distinguish one source from another source. Rule generating means provide a set of DNF rules from the patterns as a model representing each source. The test set of documents is expressed in terms of DNF rules. Evaluating means create a final classification model after minimizing any error between the DNF rules for the training and test sets. Query means enable a user to express a query in terms of features/attributes and DNF rules which when applied to the final model automatically select the optimal sources for query searching. The sources may also be expressed in taxonomic groupings which reduces the number of data sources and speeds query searching on a distributive information network by a user.
208 citations
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02 Oct 2002TL;DR: In this article, a user of a meta-search engine submits a query formulated with operators defining relationships between keywords and answers are retrieved from each source as a summary of each document found that satisfies the query.
Abstract: A user of a meta-search engine submits a query formulated with operators defining relationships between keywords. Information sources are selected for interrogation by the user or by the meta-search engine. If necessary, the query is translated for each selected source to adapt the operators of the query to a form accepted by that source. The query is submitted to each selected source and answers are retrieved from each source as a summary of each document found that satisfies the query. The answers are post-filtered from each source to determine if the answers satisfy the originally formulated query. Answers that satisfy the query are displayed as a list of selectable document summaries. The analysis includes computing a subsumption ratio of filtered answers to answers received that satisfy a translated query. The subsumption ratio is used to improve the accuracy of subsequent queries submitted by the user to the meta-search engine.
207 citations
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TL;DR: A more general version of the well-known selection problem is formulated, in which constraints on the input set are allowed and an asymptotically significant dependency on the rank of the solution element is included.
Abstract: A more general version of the well-known selection problem is formulated, in which constraints on the input set are allowed. Selection (and also ranking) problems are solved optimally for the broad class of inputs constrained to be collections of matrices with sorted rows and sorted columns.The characterization of problem complexity includes an asymptotically significant dependency on the rank of the solution element.
207 citations
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TL;DR: In this article, the authors proposed a solution of a ranking problem from Binary Comparisons, which they called the Solution of a Ranking Problem from Binary Comparison (SRC) problem.
Abstract: (1957). Solution of a Ranking Problem from Binary Comparisons. The American Mathematical Monthly: Vol. 64, No. 8P2, pp. 28-33.
207 citations